A Literature Review on Verification and Abstraction of Neural Networks Within the Formal Methods Community

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Publikace nespadá pod Fakultu sociálních studií, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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KANAV Sudeep KŘETÍNSKÝ Jan RIEDER Sabine

Rok publikování 2025
Druh Článek ve sborníku
Konference Principles of Verification: Cycling the Probabilistic Landscape : Essays Dedicated to Joost-Pieter Katoen on the Occasion of His 60th Birthday, Part III
Fakulta / Pracoviště MU

Fakulta informatiky

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Doi http://dx.doi.org/10.1007/978-3-031-75778-5_3
Popis With the increasing interest in applying neural networks (NNs) to safety-critical problems like autonomous driving or unmanned aircrafts, ensuring the reliability of these NNs becomes essential. Therefore, several verification techniques have been proposed in recent years. Additionally, various abstraction techniques have been developed to enable verification of larger NNs. As the area develops, different surveys on verification of NNs are being published. However, we are missing a systematic summarization of knowledge through the lens of formal methods. In this literature review, we provide a systematic overview of techniques for verification and abstraction of NNs published in well-known formal verification conferences during the last ten years.
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